Square Global Head of Product on: How to Build AI Agents People Actually Use, Why $49B Company Got Rid of General Managers | Willem Avé

0:00Carlos: You're reinventing the company to be a mini-day GI. Part of the vision was that basically everybody is reporting to the same person, like a super flat organization. So how realistic do you think that is? You have to kind of step back and understand why orgs exist in the first place. Willem Avé, global head of product at Square. One of the unique things about your product is that you have a hardware component as well as software. So I'm curious to know how you integrate those two orgs as part of the same function. Hardware must be approachable, must be easy to use, must be completely delightful, and doing so is not easy.

0:29Carlos: How do you make sure that someone who's not super tech savvy is able to benefit from some of this new technology that you are building? Running a business is difficult. Kind of loneliness that you don't always know where to go or what decisions to make. Square started as a payments company and now it seems like it's an entire ecosystem. How are you thinking about the larger TAM? Well, I actually have a hot take on TAM. My hot take on TAM is that... Hey, this is Carlos, CEO at Product School and your host on the Product Podcast. My guest today is Willem Ave, global head of product at Square. He landed there in 2014 when Square acquired BookFresh, the scheduling startup he co-founded and ran as CTO.

1:06Carlos: So he has watched this thing go from a little white card reader to multiple ecosystems inside block. And his customers are not on X all day. They run bakeries. Here's what we'll cover. Why they tore up the business unit model and went fully functional. The DRI model built to kill the silent veto. What happens when AI encodes the knowledge your org chart used to hold? The chatbot era is over, and what replaces it? His hot take that Tam is almost infinite. Let's get into it. Welcome to the product podcast, Willem. Thank you. Thank you for having me. Willem, so you are the global head of product at Square.

1:36Carlos: Square is part of a holding company, and maybe we can start there. You can explain a little bit more about how the companies or the teams are designed. Yeah, definitely. So I've been at Square slash Block for many years. I've seen really every evolution of the company from the little white reader all the way through to the, I think, sophisticated multiple ecosystems we have. It's, I think, unique to be at a company that has not only been able to innovate on one product, but then be able to create multiple ecosystems of products throughout its journey. And then maybe I'll just like start kind of like my journey here started, my company was acquired, I was CTO, and I kind of grew up through the engineering org here.

2:13We had a general management model for many years. So this was kind of business unit focused. And then about two years ago, we re-org the entire company to be more focused on our customers and functionalizing everything. And one of the key reasons we did that was we believed that functional excellence, i.e. excellence within your domain, engineering, product design, etc., was really important. And that some of the other org models that we had previously reduced kind of the craft and excellence that we wanted to see within each of our functions. So, yeah, the past two or so years, we've been in a fully functionalized world where there's kind of top line orgs, product design, engineering, et cetera.

2:52And within that, we have kind of brand based kind of focus areas, Square, Cash App, et cetera. And I think like from an org design perspective, there's many ways we could take the convo. But I think one of the key things is you want to kind of focus orgs around customer outcomes as much as possible. And the farther away you kind of go from that principle, I think the worst outcomes you get.

3:15Carlos: Yeah, I love this topic around org design. And I've seen so many different variations. Many companies start as functional. And then at some point, they grow and decide to go their business unit model. And then at some point, they go back to functional or some sort of hybrid in between. Yeah. So in your case today, what is part of your function? Yeah, great. So it's the Square brand. And I lead product for the Square brand. And the way that we've decided to organize the Square org is kind of just leaning into two beliefs that I have for building products. One is you want teams as close to customer outcomes as possible, right?

3:51So they can really understand the needs of the customers and be able to build products to kind of serve those needs. And that's kind of led us to a couple broad orgs. First is an audiences org. So these are all of our verticals. Think kind of services, retail, food and bev, et cetera. And then a kind of core platform org. But the core platform org importantly also has product surfaces that they're responsible for. I think it's very easy for platform teams to fall into a kind of one size fits none when they're building software. Kind of thinking about a very generic kind of solution that doesn't solve any need.

4:26So I think it's important to kind of marry product and platform together in certain areas. And then I have kind of a growth team, right? So growth, all the whole acquisition flywheel. And then a money team. So money for us is everything from bill pay, payroll, banking, et cetera. And then obviously we have kind of our hardware teams, which is a sister org to us.

4:46Carlos: Oh, I was literally going to ask about that, right? Because one of the unique things about your product is that you have a hardware component as well as software. So I'm curious to know how you integrate those two worlds as part of the same function. Yeah. So hardware, I think hardware is something very special. And we have, I think, one of the best hardware teams on the planet. And what I mean by something special is that hardware shows up in businesses' real worlds, right? It's something you put on the counter. It's something you carry with you during your shift. It's something that you use, right?

5:15So hardware must be approachable, must be easy to use. It must be completely delightful. And doing so is not easy. And I think the magic really happens when you integrate hardware and software together in a way that you can kind of build delightful experiences. Obviously, almost everyone's using an iPhone. I think they've kind of set the bar for a lot of the kind of software hardware integration. But I think the key to that is making sure that when you're building new hardware products, you're kind of marrying the software form factor with the hardware form factor. You can't think of them as completely separate, which is why I think it's difficult for companies to use kind of off the shelf component commodity hardware and build truly excellent experiences.

5:56Carlos: One of the risks I see with some works that have both hardware and software is that they're just so different that it's really hard to find a leader that can understand both worlds in depth. Similarly to what you were saying about general managers, sometimes it's just hard to find someone who really gets business and product. So in your case, I'm curious to know how you actually find the right level of support to ensure that both hardware and software are at the same level of priority. Yeah, it's a good question. So, I mean, the biggest differences to timelines are usually just different, right?

6:25Building hardware takes longer than building software. And there's different steps that you go through while building hardware and software. I think from making sure you get really great outcomes, I think you first start, you need incredible people, right? Two, you need to make sure that the process you go for building doesn't have a ton of burdensome red tape where decisions get mired either in bureaucratic process or slow decision making. because ultimately both building hardware and software is one of iteration, right? You have a vision of what you want to build, but the path there takes a bunch of different kind of turns, right?

7:03As you figure out what, you know, what defect rates you're targeting, what kind of reliability rates, et cetera, battery life, you know, there's a ton of dimensions to it. And then I think the best software is also built via kind of an iterative learning loop. So I think a lot of that, if you kind of combine both of those together, I think you can have both an org as well as a process that leads to incredible outcomes.

7:25Carlos: Block or your CEO, Jack Dorsey, has been really a pioneer in terms of how to think about org design. You recently came up with this concept of DRI. We'd love for you to expand on it. Yeah. So I think it's an incredibly interesting concept. And I think one that we've leaned into very hard. And I think it's interesting and pretty amazing is one, the best products, you have to kind of have an arc from idea to kind of scaling it. Right. And that arc is a cross-functional effort. Right. It's not just building an incredible product. It's how do you go to market with it? And then how do you keep iterating and building it?

8:05And a lot of times what happens is that products slow down because of decision making. Right. Either it's like silent vetoes throughout the org where one team doesn't want to do something that another team wants to do. Right. Or it's a lack of alignment between what we're doing or where we're going. So the DRI model is really meant to cut through decision making and effectively empower a person and an individual to see that decision making through the entire lifecycle of building building that product or solution. Now, it's a unique position, right, because you kind of have to be able to synthesize product, technology, and business and then be able to work very well across the entire arc of building that software, right?

8:46Everything from kind of ideation. I think the best ideation happens in a design and engineering led fashion where they can kind of come up and explore the entire space and then all the way through kind of like go to market and scale where you need to be able to tell the world about what you're building and why you're building it. So I think the DRI really helps shape both technical strategy, but also kind of keep the teams accountable to execution and then break down decision making. So they can cut through any sort of roadblocks or challenges that the teams may have.

9:16Carlos: I was doing my research on this model. I found a quote that said that you're reinventing the company to be a mini AGI. And part of the vision was that basically everybody is reporting to the same person, like a super flat organization. So how realistic do you think that is? Yeah, it's a good question. So I think you have to kind of step back and understand why orgs exist in the first place, right? And at least historically, orgs existed because of information flow, right? And that there needed to be a way to communicate between different orgs and teams and align them on a singular outcome, right?

9:51Whatever you're building. I think, you know, modern technology and AI has actually, you know, amplified the communication ability between a lot of the leaf nodes of a tree, so to speak. And I think the interesting thing is that whether it's everyone reporting to one person or there's, you know, for sure kind of evolutions of that. I think it's the key goal is to have small autonomous teams that are able to kind of take ownership of an outcome and build that as quickly as possible. and typically orgs are very good at like inventing process and inventing red tape because it you know meets the needs of whatever org they've created or whatever goals that org has created so i think you know and a lot of times those are for good reasons right you have a sev or a problem and then you kind of create some process to stop that from happening again i think though ai gives us the ability to encode that knowledge at another layer it doesn't have to be encoded in the org entirely.

10:50It can be encoded in data that agents have access to. And that really democratizes decision-making. It allows teams, right, small teams, I truly believe that the best teams are kind of small, fast-moving, fully autonomous and enabled teams. And it kind of enables that really to happen. You hear a lot around right now around like enterprise context graphs and things like that for AI. I think it's really just another way of saying is like, you have to encode knowledge in tools that you can have individuals and teams take advantage of that. So they don't, you don't have to play like a telephone to get an answer, right?

11:23You can get an answer from an agent and then make a decision and move forward. So I think, you know, the DRI model combined with kind of, I think, smaller, flatter kind of orgs do allow you to move a lot faster. That doesn't diminish the need of management, right? People grow in their careers. People have aspirations in their careers. You need to also have incredible managers, like people managers, right? That can help people through their kind of career growth and trajectories. So I think both of those, you kind of have to marry together, right? You need like great managers and then you need great DRIs and people that can cut through decisions so that you can deliver great products.

12:00Carlos: I think this is the time I spend the most discussing or geeking out on Oreg design because they're probably the best example of someone who is pioneering something like this and I love it. I'm also going to try to shift gears into another unique thing that I think is embedded into your product, which is you're building for the real economy. Your users are not always, you know, like, say, rev ops managers. It's also like the person that is working at the bakery, right? So tell me more about how you're thinking about that in terms of bringing AI capabilities to people who are probably not on X every single day.

12:41Yeah, the real world is definitely not on X every day. No, some are. But I think so small business is fascinating because they are like, I think, the most pure instantiation of an entrepreneur. They literally put their livelihood on the line for their passion. And that passion could be everything from like candlestick making to bakeries to really anything. And I think that's like endlessly fascinating. And I respect it a lot. I think two is that small business, in my opinion, really forms the artery or the core of the economy. I think the main streets of the world are unique. They're really important social areas for different economies and neighborhoods.

13:27And I think what Square and Block has always stood for is economic empowerment. And what that means for Square is making sure neighborhoods can thrive. And we kind of say we want Main Street to stand as tall as Wall Street. Right. And I think this is like it's really important because to do so, they need technology. Right. You can't compete today in the business landscape without, you know, help without automating parts of your business with with software and now increasingly with artificial intelligence. And I firmly believe that if you take advanced technology and democratize that, right, give that to as many people as possible, like as many small businesses as possible, that's net good for the economy and that's then net good for society, right?

14:15So I think those are some of the things that I spend a lot of time in. It's like it's not easy, right, because each of these businesses are endlessly unique, right? You build and they need very specific workflows. Like a bakery is just different than a flour shop. And that's different from a burger joint. And like they just run, you know, they have different people, they have different teams, they have different workflows. So it's all different. And I think that's one of the awesome things that we've been able to do at Square.

14:41Carlos: Well, let's try to unpack some of those use cases, because I can imagine that the level of AI adoption is different, right? So how do you make sure that someone who is not super tech savvy is able to benefit from some of this new technology that you are building for them? Yeah, so it's a good question. Running a business is difficult. And it's not difficult for like the most obvious reason. Yes, obviously, it's, you know, you have to hire and kind of do your craft, whether that be food or whatever. But it's also, it's one of kind of loneliness that you don't always know where to go or what decisions to make, right?

15:17So for example, like, what should you price a menu? What should you price your burger? Sure, you can calculate how much it costs you to make the burger, right? But should you mark it up by 10 % or 20%, right? Right. That there's an endless set of decisions. Right. Sometimes you hear kind of small business owners. They start working the second, you know, while there's while their head's still on the pillow in their bed. Right. And they keep working like, you know, all the way all the way through through the evening because there's always something. There's always some decision that they have to make.

15:45And I think the the advantage or the attraction to AI for business is not is not just a chatbot. right um it's really to have this intelligent thought partner that lets that lets businesses make better decisions right and then eventually um kind of offload and delegate full tasks to things to kind of uh parts of their business so a couple examples could be you know inventory intake or kind of um spotting sales trends for your business and then suggesting a marketing campaign or kind of a number of other kind of unique workflows. And I think the interesting part is that I think like the days of just a standard question answer chat bot are kind of over.

16:31And I think they're over for a few reasons. But first is that like, basically we've already solved that problem. And what people are expecting now is to do real work with AI, right? And real work is far more than just like answering questions and getting some answers back in a thread. Real work looks like synthesizing data across all of your data sources, it looks like kind of creating kind of artifacts specifically for your business, right? That could be something like a, you know, par inventory workflow for, for the bakery that we were talking about, or it could mean kind of a, like a sales leadership board, right?

17:05So that you can train and incentivize your, your staff, right? There's a bunch of these different artifacts. And I think that's the, that's the, that's the challenge is that it's, it's very easy to build a chatbot today. I think it's like very hard to build a dependable, reliable agent, if you will. And that's what we've been working on and really, really trying to solve. I would love to see it in action. Sure. Yeah, we can, we can, we can take it for a little, little spin. So this is ManagerBot, kind of a home screen where you can kind of come in and we, AI generates a bunch of ideas for, for, for sellers pretty kind of either, either, either daily or just in time.

17:41This is like an example of one where like, you know, add missing item descriptions and like, why is this important? Well, if you want to get found online, your online catalog needs to have great descriptions, right? So ManagerBot can notice these things and kind of like suggest descriptions. And then you can kind of go ahead and review it in chat. I'm not going to do that right this second, but I'm going to go over to computer and kind of show what I mean by doing real work, right? So this is kind of an example of, you know, maybe I want to work on some menu engineering. And rather than just a quick answer, what ManagerBot gives you is a kind of a full-on artifact, right?

18:22It does a bunch of work and it looks at both your data. It can also use a lot of other tools and, you know, it can kind of say like, okay, here are all the different items that have happened. You know, this is, you know, what you should do with each of those. These are the different types of items that are doing well or not, not doing super well. And then you can kind of like ask questions about this. Okay, great. You know, what are some suggestions based on this money? Do some research and come back with an opinion, right? And it says like, okay, this is what I would do. I would make, you know, the half pound burger a hero, not just an item, dot, dot, dot, right?

18:54So I think when someone is thinking through a problem, right, they don't just want like, okay, here is, you know, here's the answer to this. They want a richer artifact that allows them to really dig deep. I think similarly, if you look at, you know, like labor forecasts, right? So if you look at, you know, this is the labor forecast, this is all kind of demo account. You can kind of see this is where the costs are. It can actually generate very rich, rich artifacts for you. And I think this is kind of what I'm talking about. Like when sellers want to get work done, they need rich, sophisticated artifacts, right?

19:30They need real things that they can go and build themselves. Yes, that interaction might be, you know, text-based or voice, but it's much richer than just a simple answer. And I think this is when you kind of can see sellers be like, okay, this is really valuable, right? I have to put less work into the system to get some very meaningful outcomes. And then I kind of mentioned this whole ideas area where ideas are things from like sales or customer, right? Top customer relapse, two of your top customers haven't visited in 30 days. You know, there's like staff insights, inventory insights, et cetera.

20:08So this whole system working together, we feel really helps sellers both understand their business, but then also be able to take action, improve things, and then get real work done on their computer.

20:19Carlos: Thank you for going for it and showing this in action, because I think that what you mentioned around delegating to AI or getting stuff done is critical. Sometimes AI can be more work, especially if you have to be switching windows from chat GPT to PowerPoint presentation to something else. It seems like here you create that environment for them. They don't have to worry about memory MD or skills or connectors or things that maybe sound more common to the AI geeks. And so they can just continue using what they understand in a more sophisticated way. That's right. That's exactly right. I mean, I think a few things are true.

20:57One is, I love what you said, you don't want sellers or kind of customers to do more work. And I think it's a very important insight in that my experience, and I think a lot of people's experience using AI is that you just get like a bunch of word vomit. Like you get just a bunch of data and you have to like parse that. And that's actually work. Sometimes it's very useful, right? If you're doing some research or whatnot. But other times it's like, please shorten that for me or just like create me a little website or something, right? And I think the more that you can steer these experiences to very high value that doesn't cause customers to do a lot of work to use that, that builds trust with the system.

21:37And then it allows you to delegate and take actions. I didn't show this in the demo, but you can do bulk actions. You can create campaigns. You can do all that other great stuff kind of within the same experience. But I think one of the interesting things, at least for small business, is a lot of times people don't just wake up and like, oh, I have to change the price of X. Usually you have to do like some investigation. Right. So you want to kind of like get some questions and, you know, kind of like get some detailed analyses. And then you have enough trust in the system to be like, OK, now I'll go delegate some work to it to go actually execute on inventory counts or price changes or whatnot.

22:13Carlos: So I'm thinking about your overall time, right, because in a way, Square started as a payments company. And now it seems like it's an entire ecosystem. So how are you thinking about that and the larger TAM? Yeah. Well, I actually have a hot take on TAM. And my hot take on TAM is that I think with the right team, with the right idea and the right kind of learning loop, your TAM is almost infinite. What I mean by that is that you can create markets, right, with incredible products. And I think that that's important for Square in that we have effectively endless TAM. And, you know, because it's the it's the small, medium, even enterprise economy, right, which is trillions of dollars.

22:54And I think I think that the two important things for building kind of products and software in these like very large TAM markets is one, you need some forcing function to help teams and people make decisions. So we we at Square believe in local economies and neighborhoods. And our North Star is to build what we call a neighborhood network. And a neighborhood network is effectively all the economic action that happens in a neighborhood, right? And that's small business owners, that's their staff, and that's the customers coming into those businesses. The interesting thing around focusing on local neighborhoods is it actually refocuses the TAM away from some things like internet-only direct-to-consumer websites, right?

23:41That's not part of a local economy. and what you can actually start to do is look at look at Main Street look at your local neighborhoods and kind of see what kinds of businesses that exist there right so then you have you have kind of a you know an ideal customer right these are the sets of customers that I want to go build for and then you can actually help teams make decisions about okay great we're going to solve those needs and we're going to solve those needs across kind of commerce tools right both online and offline financial tools right banking checking kind of you know credit all those those tools and then intelligence tools right because intelligence and autonomy is a core part of building software and helping local neighborhoods be better because today i see the current smb to

24:26Carlos: have a lot of fragmented point solutions they might have their website builder they might have their yelp page or something similar where they can see reviews right they have their reservation or point of sales, technology, and maybe some others in between. So if I understand correctly, we are talking about a full-on integration that allows the small business owner to have access to technology without having to worry too much about these smaller pieces of point solutions. That's right. So I think the challenge for that is at least it used to be very difficult to be able to build software for each of those quadrants.

25:02I think AI software engineering has kind of lowered that bar to a certain degree. I think the second point is that a lot of customers and sellers have software solutions today that they like, right? So for us to be successful, we need both great first party tools, right? That's point of sale, kind of staff management tools, et cetera, but also have a very open platform to allow all of our incredible partners to build alongside us, right? And with us so that we can help reduce like, you know, a bunch of tabs and copying data between this tool and that tool to help you answer a question. And then I think the third is that AI, at least, you know, kind of agentic AI really allows sellers to interact with a bunch of different software products at the same time, because a lot of software is, it's kind of able to be used very well by agentic tools.

25:54You see that today with Claude and Codex, et cetera. Like it can just use these tools exceedingly well. So it's, it's helping solve a lot of this multi, multi-software challenges that customers have.

26:06Carlos: Maybe it's because I'm on vacation this week. I'm in Turkey and it's crazy. I had to make a hair appointment the other day and they sent me to WhatsApp and I had to message the hairdresser literally on WhatsApp. And then the other day I wanted to make a dinner reservation and the open table and all of those websites are not very popular here. So I had to message them on Instagram. So I'm also very curious about how you're thinking about the communication tools. Especially for emerging markets. Yeah, no, it's a great question. So I think a few things, like business at its core is a kind of communication slash team sport, right?

26:45Like you want to communicate with your customers. You need to communicate with your staff. Today, a lot of that communication happens in very segmented siloed tools, right? Like you just mentioned, that's going to be WhatsApp, Instagram, email. Like I got to go, you know, I need a contractor to go fix something. It's usually email, maybe it's text. So I think it's like, and when you talk to business owners, they are drowning in these like many different communication tools, right? They're like, my SMS inbox is like hundreds of unreads. And I guess it's crazy, right? Just, I mean, just your example is business.

27:18I mean, imagine that business is WhatsApp thing, right? It's probably crazy. So I think, I think one is no one's really solved this yet. I think just to be honest, I think, too, I'm pretty interested in trying to solve it for small businesses. And I think there's some very cool collaboration platforms that I think we're building. One is Buzz that I think actually is pretty unique and pretty interesting to think about how, maybe not that exact product, but how that model could help sellers, right? Manage both their staff, but also manage a lot of communication in bounds across a lot of these different channels that they get.

27:54Carlos: Yeah. We were also very curious to know, because that is a very, very new product that Block announced. And it seems to be going so many different angles, right? Like one is what you just described. Another one could be potentially replacement of Slack for different types of businesses. But it seems like in a way you are trying to create a limited time. Yeah. I think, I mean, I'll just go back to like, you know, every business and every person has a communication challenge, right? Not like actually talking, right? But actually like managing all of the different channels. And I don't think we have a great solution yet.

28:25I think I'm pretty excited about the Buzz technology for a lot of good reasons. I think it's something that we're kind of excited to work on.

28:34Carlos: William, it's been a pleasure to have you on the pod. Thank you so much for your time. Yeah, thank you for having me. It's been great.